Affiliation: Gillings School of Global Public Health, Department of Epidemiology
Disparities in HIV incidence are seen by race and sexual orientation, although race and sexual orientation do not sufficiently explain differential risk within sexual networks. Race and sexual orientation, however, influence partner selection, risk behavior, and access to care. Partner selection and risk behavior underlay differences in HIV acquisition and can be studied within the context of a sociosexual network. Marginalized or stigmatized persons are more likely to be diagnosed with HIV later in the course of infection and less likely to achieve viral suppression, which both increase the amount of time that a person remains infectious.
Infectious persons who are active in a sexual network risk onward transmission of HIV, becoming superinfected, or acquiring another sexually-transmitted infection (STI) such as syphilis, which has a synergistic effect with HIV. Knowing the HIV prevalence within high-risk sexual networks, HIV and STI history of network members, and partnership patterns may provide sufficient information to guide targeted interventions to reduce the amount of time that HIV-positive persons remain infectious.
This study uses newly diagnosed HIV cases reported 2012-2013 to create a “baseline” sexual network. We examined HIV transmission cluster involvement and followed new cases through 2016 for post-baseline partnerships investigated for public health HIV prevention efforts as a marker for transmission risk potential. Network structure and partner selection behaviors were modeled to predict which cases were likely to be involved in a transmission event and were a candidate for enhanced linkage to care support.
PUBLIC HEALTH SIGNIFICANCE
Too few diagnosed HIV cases in the United States are in care and virally suppressed, thereby increasing the likelihood of onward transmission. Identifying factors associated with HIV acquisition and transmission by following persons in the sexual network or assessing transmission cluster growth may help us understand how partnerships form and whether any baseline network structures predict remaining active in high-risk sexual networks.